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Robust Operation of Hybrid Solar–Wind Power Plant with Battery Energy Storage System

Author

Listed:
  • Mostafa Bakhtvar

    (Future Operations, Innovation and Planning, EirGrid Plc., D04 FW28 Dublin, Ireland)

  • Amer Al-Hinai

    (Electrical & Computer Engineering, Sultan Qaboos University, Al Khoud, Muscat 123, Oman)

Abstract

The intraday continuous electricity market (ICM) is a potential target market for the Dispatchable Hybrid Renewable solar–wind–battery energy storage system (BESS) power plant (DHRB). However, the uncertainty of the electricity price jeopardizes economic justification of BESS operation, an essential component of DHRB. Using the duality theory, this paper proposes a unilevel mixed-integer linear programming rolling-approach-based robust optimal scheduling tool for DHRB that keeps BESS operation optimal should the worst price scenario occur. It reflects BESS’s degradation as penalty factors and also integrates a BESS degradation model in the scheduling tool for better assessment of the available resources through the BESS’s lifetime. This tool aids the DHRB operator to decide the power offer to the ICM in such a way that the BESS’s operation remains optimal. A case study is carried out to demonstrate the application of the proposed tool. Both the long-term and short-term losses/benefits of utilizing this tool for scheduling DHRB in the ICM are investigated at various uncertainty levels. It is shown that there will be a risk of loss of income for the DHRB in the short-term due to increased nondispatchable energy. However, by limiting the use of BESS to only those settlement periods that are either certainly profitable or unavoidable, the lifetime of BESS can potentially be extended. Hence, this can result in more income by the DHRB power plant in the long-term.

Suggested Citation

  • Mostafa Bakhtvar & Amer Al-Hinai, 2021. "Robust Operation of Hybrid Solar–Wind Power Plant with Battery Energy Storage System," Energies, MDPI, vol. 14(13), pages 1-18, June.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:13:p:3781-:d:580886
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    References listed on IDEAS

    as
    1. Abdullah Al Shereiqi & Amer Al-Hinai & Mohammed Albadi & Rashid Al-Abri, 2020. "Optimal Sizing of a Hybrid Wind-Photovoltaic-Battery Plant to Mitigate Output Fluctuations in a Grid-Connected System," Energies, MDPI, vol. 13(11), pages 1-21, June.
    2. Karsten Neuhoff & Nolan Ritter & Aymen SalahAbou-El-Enien & Philippe Vassilopoulos, 2016. "Intraday Markets for Power: Discretizing the Continuous Trading?," Working Papers EPRG 1609, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    3. Li, Gong & Shi, Jing & Qu, Xiuli, 2011. "Modeling methods for GenCo bidding strategy optimization in the liberalized electricity spot market–A state-of-the-art review," Energy, Elsevier, vol. 36(8), pages 4686-4700.
    4. Saira Al-Zadjali & Ahmed Al Maashri & Amer Al-Hinai & Sultan Al-Yahyai & Mostafa Bakhtvar, 2019. "An Accurate, Light-Weight Wind Speed Predictor for Renewable Energy Management Systems," Energies, MDPI, vol. 12(22), pages 1-20, November.
    5. Bertrand, Gilles & Papavasiliou, Anthony, 2020. "Adaptive Trading in Continuous Intraday Electricity Markets for a Storage Unit," LIDAM Reprints CORE 3104, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. Fleten, Stein-Erik & Kristoffersen, Trine Krogh, 2007. "Stochastic programming for optimizing bidding strategies of a Nordic hydropower producer," European Journal of Operational Research, Elsevier, vol. 181(2), pages 916-928, September.
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    Cited by:

    1. Chaoyang Chen & Hualing Liu & Yong Xiao & Fagen Zhu & Li Ding & Fuwen Yang, 2022. "Power Generation Scheduling for a Hydro-Wind-Solar Hybrid System: A Systematic Survey and Prospect," Energies, MDPI, vol. 15(22), pages 1-31, November.
    2. Ana Rita Silva & Ana Estanqueiro, 2022. "From Wind to Hybrid: A Contribution to the Optimal Design of Utility-Scale Hybrid Power Plants," Energies, MDPI, vol. 15(7), pages 1-19, April.

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